When training a CNN, what are the hyperparameters to tune first?
Firstly when you say an object detection CNN, there are a huge number of model architectures available. Considering that you have narrowed down on your model architecture a CNN will have a few common layers like the ones below with hyperparameters you can tweak:


Convolution Layer:- number of kernels, kernel size, stride length, padding
MaxPooling Layer:- kernel size, stride length, padding
Dense Layer:- size
Dropout:- Percentage to keep/drop